Try this This is for Oracle but should work for MSSQL. If you want ordering then do it on DF
val d = HiveContext.load("jdbc", Map("url" -> _ORACLEserver, "dbtable" -> "(SELECT to_char(ID) AS ID, to_char(CLUSTERED) AS CLUSTERED, to_char(SCATTERED) AS SCATTERED, to_char(RANDOMISED) AS RANDOMISED, RANDOM_STRING, SMALL_VC, PADDING FROM scratchpad.dummy)", "user" -> _username, "password" -> _password)) *d.sort(asc("ID")).registerTempTable("tmp")* I believe that will work. HTH Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com On 20 June 2016 at 12:10, Takeshi Yamamuro <linguin....@gmail.com> wrote: > Hi, > > Currently, no. > spark cannot preserve the order of input data from jdbc. > If you want to have the ordered ids, you need to sort them explicitly. > > // maropu > > On Mon, Jun 20, 2016 at 7:41 PM, Ashok Kumar <ashok34...@yahoo.com.invalid > > wrote: > >> Hi, >> >> I have a SQL server table with 500,000,000 rows with primary key (unique >> clustered index) on ID column >> >> If I load it through JDBC into a DataFrame and register it >> via registerTempTable will the data will be in the order of ID in tempTable? >> >> Thanks >> > > > > -- > --- > Takeshi Yamamuro >